Current production techniques for focal plane arrays (FPAs) show a non-linear relationship between cost and production yield. An FPA with 99.5% good (or compliant) pixels/picture elements costs significantly more than an FPA with 98.5% good pixels. As the number of operational pixels required in an FPA increases, production yields begin to drop off. This drives up the cost of an FPA and also drives up maintenance or replacement costs as pixels fail or are identified as defective within an FPA.
Current techniques for pixel value replacement or approximation employ techniques such as selecting the value of a neighboring pixel or otherwise making an approximation of what the missing pixel value should be based on weighted averages and/or interpolation techniques. Such techniques, however, are not well-suited for detection and tracking solutions as their main purpose is to eliminate artifacts in still images.